There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation.

Summary Paragraph Sensory, motor, and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures1,2. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution but from only a few dozen neurons per shank. Optical Ca2+ imaging3–5 offers more coverage but lacks the temporal resolution to reliably distinguish individual spikes and does not measure local field potentials. To date, no technology compatible with unrestrained animals has combined high spatiotemporal resolution with large volume coverage. To satisfy this need, we designed, fabricated, and tested a new silicon probe called Neuropixels. Each probe has 384 recording channels that can programmably address 960 CMOS processing-compatible low-impedance TiN6 sites that tile a single 10 mm long, 70x20 µm cross section shank. The 6x9 mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed, and digitized on the base, allowing noise-free digital data transmission directly from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were simultaneously recorded from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed recording large populations of neurons from multiple brain structures in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens the path to record brain-wide neural activity during behavior.

Neuronal populations in sensory cortex produce variable responses to sensory stimuli, and exhibit intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables. Recording over 10,000 neurons in mouse visual cortex, we observed that spontaneous activity reliably encoded a high-dimensional latent state, which was partially related to the mouse’s ongoing behavior and was represented not just in visual cortex but across the forebrain. Sensory inputs did not interrupt this ongoing signal, but added onto it a representation of external stimuli in orthogonal dimensions. Thus, visual cortical population activity, despite its apparently noisy structure, reliably encodes an orthogonal fusion of sensory and multidimensional behavioral information.

Summary An increasingly powerful approach for studying brain circuits relies on targeting genetically encoded sensors and effectors to specific cell types. However, current approaches for this are still limited in functionality and specificity. Here we utilize several intersectional strategies to generate multiple transgenic mouse lines expressing high levels of novel genetic tools with high specificity. We developed driver and double reporter mouse lines and viral vectors using the Cre/Flp and Cre/Dre double recombinase systems, and established a new, retargetable genomic locus, TIGRE, which allowed the generation of a large set of Cre/tTA dependent reporter lines expressing fluorescent proteins, genetically encoded calcium, voltage, or glutamate indicators, and optogenetic effectors, all at substantially higher levels than before. High functionality was shown in example mouse lines for GCaMP6, YCX2.60, VSFP Butterfly 1.2, and Jaws. These novel transgenic lines greatly expand the ability to monitor and manipulate neuronal activities with increased specificity.

Simple cells in the primary visual cortex often appear to compute a weighted sum of the light intensity distribution of the visual stimuli that fall on their receptive fields. A linear model of these cells has the advantage of simplicity and captures a number of basic aspects of cell function. It, however, fails to account for important response nonlinearities, such as the decrease in response gain and latency observed at high contrasts and the effects of masking by stimuli that fail to elicit responses when presented alone. To account for these nonlinearities we have proposed a normalization model, which extends the linear model to include mutual shunting inhibition among a large number of cortical cells. Shunting inhibition is divisive, and its effect in the model is to normalize the linear responses by a measure of stimulus energy. To test this model we performed extracellular recordings of simple cells in the primary visual cortex of anesthetized macaques. We presented large stimulus sets consisting of (1) drifting gratings of various orientations and spatiotemporal frequencies; (2) plaids composed of two drifting gratings; and (3) gratings masked by full-screen spatiotemporal white noise. We derived expressions for the model predictions and fitted them to the physiological data. Our results support the normalization model, which accounts for both the linear and the nonlinear properties of the cells. An alternative model, in which the linear responses are subject to a compressive nonlinearity, did not perform nearly as well.Key words: visual cortex; contrast; nonlinearity; gain control; normalization; masking; noise A longstanding view of simple cells in the primary visual cortex is that they compute a weighted sum of the light intensities falling on their receptive field (Hubel and Wiesel, 1962;Movshon et al., 1978a; C arandini et al., 1997b). This linear model is depicted in Figure 1 A and is usually taken to include a rectification (thresholding) stage to account for the transformation of intracellular signals into firing rates.Although many aspects of simple cell responses are consistent with the linear model, there also are important violations of linearity. For example, scaling the contrast of a stimulus would identically scale the responses of a linear cell. At high contrasts, however, the responses of simple cells show clear saturation . Moreover, simple cells are subject to cross-orientation inhibition; the responses to an optimally oriented stimulus can be diminished by superimposing an orthogonal stimulus that is ineffective in driving the cell when presented alone (Morrone et al., 1982;Bonds, 1989;Bauman and Bonds, 1991).According to a view that has emerged in recent years, the nonlinearities of simple cells could be explained by extending the linear model to include a gain control stage (Albrecht and Geisler, 1991;Heeger, 1991Heeger, , 1992bHeeger, , 1993DeAngelis et al., 1992;Carandini and Heeger, 1994;Nestares and Heeger, 1997; Tolhurst and Heeger, 1997a,b). In particular, one of us (Heeger, 1...

Two-photon microscopy of calcium-dependent sensors has enabled unprecedented recordings from vast populations of neurons. While the sensors and microscopes have matured over several generations of development, computational methods to process the resulting movies remain inefficient and can give results that are hard to interpret. Here we introduce Suite2p: a fast, accurate and complete pipeline that registers raw movies, detects active cells, extracts their calcium traces and infers their spike times. Suite2p runs on standard workstations, operates faster than real time, and recovers ~2 times more cells than the previous state-of-the-art method. Its low computational load allows routine detection of ~10,000 cells simultaneously with standard twophoton resonant-scanning microscopes. Recordings at this scale promise to reveal the fine structure of activity in large populations of neurons or large populations of subcellular structures such as synaptic boutons.

The temporal features of tactile stimuli are faithfully represented by the activity of neurons in the somatosensory cortex. However, the cellular mechanisms that enable cortical neurons to report accurate temporal information are not known. Here, we show that in the rodent barrel cortex, the temporal window for integration of thalamic inputs is under the control of thalamocortical feed-forward inhibition and can vary from 1 to 10 ms. A single thalamic fiber can trigger feed-forward inhibition and contacts both excitatory and inhibitory cortical neurons. The dynamics of feed-forward inhibition exceed those of each individual synapse in the circuit and are captured by a simple disynaptic model of the thalamocortical projection. The variations in the integration window produce changes in the temporal precision of cortical responses to whisker stimulation. Hence, feed-forward inhibitory circuits, classically known to sharpen spatial contrast of tactile inputs, also increase the temporal resolution in the somatosensory cortex.

Vision, choice, action, and behavioral engagement arise from neuronal activity that may be distributed across brain regions. Here we delineate the spatial distribution of neurons underlying these processes. We used Neuropixels probes 1,2 to record from ~30,000 neurons in 42 brain regions of mice performing a visual discrimination task 3. Neurons in nearly all regions responded non-specifically when the mouse initiated an action. By contrast, neurons encoding visual stimuli and upcoming choices occupied restricted regions in neocortex, basal ganglia, and midbrain. Choice signals were rare and emerged with indistinguishable timing across regions. Midbrain neurons were activated before contralateral choices and suppressed before ipsilateral choices, whereas forebrain neurons could prefer either side. Brain-wide pre-stimulus activity predicted engagement in individual trials and in the overall task, with enhanced subcortical but suppressed neocortical activity during engagement. These results reveal organizing principles for the distribution of neurons encoding behaviorally relevant variables across the mouse brain. Performing a perceptual decision involves processing sensory information, selecting actions that may lead to reward, and executing these actions. It is unknown how the neurons mediating these processes are distributed across brain regions, and whether they rely on circuits that are shared or distinct. Most studies of action selection (here referred to simply as choice) have focused on individual regions such as frontal, parietal, and motor cortex, basal ganglia, thalamus, cerebellum, and superior colliculus 4-11. However, neural correlates of movements, rewards, and other task variables have been observed in multiple brain regions, including in areas previously identified as purely sensory 12-24. It is therefore Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: